1. Field of the Invention
The present disclosure relates to a technique of recognizing a spatial distribution of one or more preceding vehicles by using a radar.
2. Description of the Related Art
Conventionally, onboard radar systems have utilized radars of various electronic scanning types which are based on the methods including FMCW (Frequency Modulated Continuous Wave) radar, multiple frequency CW (Continuous Wave) radar, and pulse radar, for example. In such radar systems, generally speaking, a modulated continuous wave, or alternatively a pulse wave, is emitted from a transmission antenna as a “transmission wave”, and an arriving wave that is reflected from a preceding vehicle and returns to the reception antenna is received as a “reception wave”. Then, from an antenna signal (reception signal) that is based on the reception wave, the position and velocity of the preceding vehicle are estimated. With reference to the vehicle having the radar system mounted thereon, the position of a preceding vehicle is defined by a distance (“range”) between the vehicle having the radar system mounted thereon and the preceding vehicle, and the direction of the preceding vehicle. In the present specification, the vehicle having the radar system mounted thereon is referred to as “the driver's vehicle”, whereas any vehicle traveling before or ahead of the driver's vehicle is referred to as a “preceding vehicle”. It is assumed that a “preceding vehicle” may be traveling in the same lane as the driver's vehicle, or in an adjoining lane containing traffic traveling in the same direction as the driver's vehicle.
In an onboard radar system, the “direction” of a preceding vehicle can be defined by an azimuth within an approximate plane containing the road. Therefore, in the present specification, for a given object that is detected by a radar, the terms “direction” and “azimuth” may be synonymously used.
The direction of a preceding vehicle can be expressed by an angle of the direction of arrival (DOA: Direction Of Arrival)” of an arriving wave. In the field of radar technology, an object that reflects a transmission wave, such as a preceding vehicle, may be referred to as a “target”. The target functions as a wave source of the “reflected wave”. The target is a signal source of a wave that arrives at the reception antenna, i.e., a reception wave.
In a radar system for onboard use, a small-sized and inexpensive antenna is desirable. For example, an array antenna composed of four or five antenna elements is used as a receiving antenna. Depending on the manner in which the antenna elements are arrayed, an array antenna can be categorized into a linear array type, a planar array type, a circular array type, or a conformal array type.
Based on the reception signals which are obtained from the respective antenna elements in the array antenna, it is possible through a signal processing technique to estimate the azimuth (direction of arrival) of an object that reflects the transmission wave. However, in the case where plural objects exist to reflect a transmission wave, the wave reflected off each object will impinge on the reception antenna at a different angle. Therefore, the reception antenna will produce a complicated signal in which a plurality of arriving waves are superposed. Moreover, in an onboard radar system, the relative positioning and distance of an object, as taken with respect to the array antenna, change dynamically. Therefore, in order to accurately estimate the respective azimuth(s) of one or plural preceding vehicles based on the reception signals at the array antenna, a huge amount of computation needs to be rapidly done by a computer.
In order to estimate the direction of arrival, various algorithms for processing the reception signals at an array antenna have been proposed. Known algorithms for direction-of-arrival estimation include the following methods (see Japanese Laid-Open Patent Publication No. 2009-156582 and Japanese Laid-Open Patent Publication No. 2006-275840).
(1) Digital Beam Former (DBF) method
(2) Capon method
(3) linear prediction coding method
(4) minimum norm method
(5) MUSIC (MUltiple SIgnal Classification) method
(6) ESPRIT (Estimation of Signal Parameters via Rotational Invariance Techniques)) method
Generally speaking, as the angular resolution of direction estimation increases, an increased amount of computation becomes needed for signal processing. In the aforementioned methods of direction-of-arrival estimation (1) to (6), angular resolution increases in the order from method (1) to method (6), thus requiring so much more computational processing. The MUSIC method and the ESPRIT method, which provide particularly high angular resolutions and are also called “super-resolution algorithms”, require rapidly subjecting the reception signals at the array antenna to processes that require large computation amounts. Specifically, under a super-resolution algorithm, a spatial covariance matrix is generated from the data of respective reception signals at the array antenna. Then, through eigenvalue decomposition of this spatial covariance matrix, the direction of arrival of the reception wave is estimated. Eigenvalue decomposition of a matrix involves decomposing the matrix into a diagonal matrix having eigenvalues as its diagonal components. When a spatial covariance matrix is subjected to eigenvalue decomposition, eigenvalues and eigenvectors of the spatial covariance matrix are obtained (see, for example, Japanese Laid-Open Patent Publication No. 2006-047282).
The estimation accuracy of a direction of arrival improves as more noise components are removed from the spatial covariance matrix. Since it can be assumed from ergodicity that an ensemble average equals a time average, a spatial covariance matrix is generated by using a time average of received data. For example, in the case of an FMCW radar, it is preferable to maximize the number of samples, i.e., number of snapshots, for the data set of beat signals (that is, chronological data within a certain time slot which can be converted into frequency domain data), thus to utilize an averaged-out spatial covariance matrix. Thus, in order to enhance the accuracy of estimation of a direction of arrival in a situation where the position of a preceding vehicle may always be changing, rapid sampling needs to be performed, thus requiring greater memory capacity for the sampled data.
Super-resolution algorithms, e.g., MUSIC, require large amounts of computational processing. Expensive microprocessors for onboard use that can rapidly operate in order to handle such large amounts of computational processing are required. Due to such circumstances, attempts to reduce the amount of computational processing have been made in order to enable operation using microprocessors with relatively low performance (see, for example, Japanese Laid-Open Patent Publication No. 2007-040806).
However, even if the amount of computational processing is reduced by the technique of Japanese Laid-Open Patent Publication No. 2007-040806 or the like, there still remains a large amount of computational processing. Thus, a technique of target recognition is needed for radars for onboard use which requires an even smaller amount of processing.